「search run」の検索結果

Interact with DeerFlow AI agent platform via its HTTP API. Use this skill when the user wants to send messages or questions to DeerFlow for research/analysis, start a DeerFlow conversation thread, check DeerFlow status or health, list available models/skills/agents in DeerFlow, manage DeerFlow memory, upload files to DeerFlow threads, or delegate complex research tasks to DeerFlow. Also use when the user mentions deerflow, deer flow, or wants to run a deep research task that DeerFlow can handle.

日本語の概要は準備中です。原文の説明を表示しています。

macOSのThings 3で、今日の予定や受信箱を確認し、タスクの追加・検索・更新を行うスキル。メモ、期限、タグ、チェックリストも扱えます。

• 今日の予定と受信箱を確認したいとき
• 期限やチェックリスト付きのタスク登録
• 既存タスクを検索・更新したいとき

ベンガル語の検索やAI向けに、文字表現の統一、単語分割、数字変換、結合文字を壊さない表示処理を整理し、学習データの整備や保存にも役立つスキル。

• ベンガル語の検索や入力を実装したいとき
• ベンガル語の学習データ整備
• ベンガル語と英語の会話対応

機能追加やコード整理の後に、ビルド・型・lint・テスト・秘密情報の検索・差分を6段階で確認するスキル。合否と修正事項をまとめ、PRを作成できる状態か報告します。

• 機能追加後のコードを検証したいとき
• リファクタリング後の不具合確認
• PR作成前の準備状況確認

大きな機能の設計提案を、依存関係と合格条件を持つ作業単位に分け、複数エージェントの調査・実装・テスト・レビューから統合と最終検証まで整理するスキル。

• 大きな設計提案を検証可能な作業に分けたいとき
• 複数エージェントへの依存関係付き作業割り当て
• 変更ブランチのレビューと順次統合

候補の探索や比較を繰り返し、試行の根拠と判断を追記型の台帳に残すスキル。前回との整合性や再検証の結果を確認し、実取引や本番操作へ進む条件を明確にします。

• 試行を重ねて候補を比較したいとき
• 判断の根拠を記録したいとき
• 新情報で前回の採用候補を見直したいとき

ユーザーや状況に合う上位候補を選ぶ推薦・ランキング処理を、候補取得から採点、選択、記録までの6段階で設計し、動くコードのひな形にするスキル。

• 個人向けコンテンツ配信の設計
• 検索やRAGの結果を並べ替えたいとき
• タスクの優先順位付け

処理の高速化を、現状の計測、仮説ごとの変更案の比較、正しさの検証へ分解し、時間や費用の上限内で最も速い安全な案と再実行できる手順を残すスキル。

• 遅い処理を計測しながら高速化したいとき
• 同じ入力条件で実装案を比較したいとき
• 応答時間・処理量・実行費用の評価

Run the first-run setup chat in the Hermes desktop app.

日本語の概要は準備中です。原文の説明を表示しています。

クラウド上のGPUで機械学習の学習・推論を実行し、モデルをAPIとして公開するスキル。Pythonで実行環境を定義し、並列処理や定期実行も設定できます。

• GPUサーバーを管理せず学習したいとき
• モデルを自動拡張するAPIとして公開
• 大量のデータを並列処理したいとき

Pythonの実行を途中で止め、変数や処理の流れを調べて不具合の原因を探ります。pdbとdebugpyを使い分け、失敗したテストや稼働中のプロセスも調査します。

• 失敗したテストの変数を調べたいとき
• 関数内のコレクションの変化を追う
• 例外発生地点の変数の確認

Microsoft Teamsの会議を要約し、対応事項を抽出します。要約が届かない原因の確認や、保存済み処理の再実行、会議通知の購読管理も支援するスキル。

• 会議の要約と対応事項の抽出
• 会議要約が届かない原因調査
• 失敗した会議処理の再実行

数学の概念や数式の導出、アルゴリズムの動きをアニメーション動画にします。構成づくりから描画、動画の結合まで、図形で理解を促す解説を制作します。

• 数学の概念を図形で説明したいとき
• 数式の導出を順に見せたいとき
• アルゴリズムの動きを可視化

Use when a task is too large for one model pass, needs parallel research or generation across many subtasks (like researching a dozen competitors at once), or the user asks to orchestrate multiple models, split work across a model team, run an advisor-worker loop, have a stronger model review the plan while cheap workers execute, or says "too big for one model" or "fan this out". Not for single-file edits or tasks one model handles in one pass.

日本語の概要は準備中です。原文の説明を表示しています。

Create and maintain agent-authored Paperclip status cards, or compile a prose interest prompt into bounded CompanySearchQuery objects and write the first summary from the assigned Summarizer run.

日本語の概要は準備中です。原文の説明を表示しています。

Run the CCS Align seat's hourly breathing cycle — prove the local claude-mem worker is healthy, pull needle observations through search → timeline → get_observations, land them in a seat-owned middle cache via atomic grab → append → filter exclude-marks → replace, manage exclude marks, and walk house → project → seat rules to detect conflicts (SHADOW_HOUSE, DENY_ALLOW, DRIFT, CLOCK_HEADER) with an append-only rules-report.md. Use when asked to run CCS Align, breathe the alignment seat, refresh the middle cache, exclude or restore an observation, walk rules, check rules conflicts, or check the Worker Watch board.

日本語の概要は準備中です。原文の説明を表示しています。

Search, install, and wire registry blocks and components into HyperFrames compositions. Use BEFORE hand-building any named visual — whenever a brief, a user, or a storyboard names a look, effect, treatment, or transition such as CRT scanlines, glitch, chromatic aberration, film grain, a shimmer sweep, a chart, a code or terminal window, a map, or a confetti burst — because roughly 400 hosted items already cover many of them and the search ranks all of them with nothing installed, no project, and no account. Also use when running hyperframes add or hyperframes catalog, installing one item or every block matching a tag, wiring an installed item into index.html, or working with hyperframes.json. Covers discovery, install locations, block sub-composition wiring, component snippet merging, and authoring a new block or component to contribute upstream (idea → scaffold → validate → PR).

日本語の概要は準備中です。原文の説明を表示しています。

When the user wants to create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'deal-specific ROI analysis,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' 'buyer persona card,' 'battle card,' 'battlecard,' 'competitive one-pager,' 'win-loss analysis,' 'why are we losing deals,' 'loss reasons,' 'how do I respond to this objection,' 'prospect just said,' 'help my sales team,' 'sales materials,' or 'what should I give my sales reps,' 'cold call script,' or 'voicemail script.' Use this for any document or asset that helps a sales team close deals. For public competitor comparison pages, see competitors. For running buyer interviews or churn research, see customer-research. For marketing website copy, see copywriting. For cold outreach emails, see cold-email. For the offer being sold (bonuses, guarantees, pricing structure), see offers.

日本語の概要は準備中です。原文の説明を表示しています。

Interact with Obsidian vaults using the Obsidian CLI to read, create, search, and manage notes, tasks, properties, and more. Also supports plugin and theme development with commands to reload plugins, run JavaScript, capture errors, take screenshots, and inspect the DOM. Use when the user asks to interact with their Obsidian vault, manage notes, search vault content, perform vault operations from the command line, or develop and debug Obsidian plugins and themes.

日本語の概要は準備中です。原文の説明を表示しています。

Applies Arbor Hypothesis Tree Refinement to research artifacts with repeatable evaluators, including model training, agent harnesses, data synthesis and benchmark optimization. Uses persistent hypotheses, isolated experiments, evidence propagation and held-out candidate comparison for multi-experiment research runs. Includes a standard-library state manager and guidance for the RUC-NLPIR Arbor CLI.

日本語の概要は準備中です。原文の説明を表示しています。

Finds grant and solicitation opportunities the organization actually qualifies for, runs a hard go/no-go before anyone starts writing, drafts the application or response from past submissions and real program data, and tracks every deadline and reporting obligation that follows an award. Built for nonprofits, government contractors, and education, and it filters daily feeds like SAM.gov or DIBBS down to the handful worth bidding. Runs on Google Drive or M365 with DocuSign and Calendar deepening it, and works from uploaded past submissions plus web research when nothing is connected. Use this whenever a funding or bidding opportunity is in play — including "find grants we qualify for," "should we bid this," "draft the response to this RFP," "we've got 50 solicitations to filter," "what's due on the federal grant," or "help me write the proposal narrative."

日本語の概要は準備中です。原文の説明を表示しています。

Analyze or explore a codebase (remote or local repository) by packing it with the Repomix CLI, then reading and searching the generated output. Use when the user wants a high-level understanding of an unfamiliar or large repo, not a targeted edit. Trigger for: - Structure/overview: "analyze this repo", "what's the structure", "explain this codebase", "what's in vercel/next.js" - Pattern discovery across many files: "find all auth code", "where are the API endpoints", "show me all React components" - Metrics: "how many files/tokens", "largest files", "TypeScript vs JavaScript ratio" - Remote repos: any github.com URL or "owner/repo" the user wants explored DO NOT trigger for: - Editing, refactoring, or writing code in the current project - Reading or searching a known file/path in the local project (use Read or grep directly) - Single-symbol lookups in the local project answerable with one grep - Git operations, running tests, builds, or installs

日本語の概要は準備中です。原文の説明を表示しています。

Runbook for turning a new HubSpot lead into a researched, personalized follow-up email and a proposed call slot for {{projectName}}. Covers company research, the sales playbook (positioning, tone, qualifying questions), HubSpot record updates, Google Calendar availability, and the human approval gate before anything sends.

日本語の概要は準備中です。原文の説明を表示しています。

Runbook for turning a new HubSpot lead in {{hubspot_list}} into a researched, personalized outbound sequence for {{projectName}}. Covers enrichment research, the outreach playbook (angles, proof points, what to avoid), sequence drafting, HubSpot logging, the daily cap, and the human approval gate before anything sends.

日本語の概要は準備中です。原文の説明を表示しています。